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Introduction to R Programming for Data Science

Master R programming fundamentals for data science with hands-on practice in data manipulation and analysis.

Master R programming fundamentals for data science with hands-on practice in data manipulation and analysis.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM Data Analytics with Excel and R Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.5

(450 ratings)

45,785 already enrolled

Instructors:

English

پښتو, বাংলা, اردو, 3 more

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Introduction to R Programming for Data Science

This course includes

10 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Learn basic R programming syntax and data types

  • Master common data structures like vectors, matrices, and data frames

  • Implement program control flow with conditions and loops

  • Create custom functions for data manipulation

  • Import and export data from various file formats

  • Perform web scraping and API requests

Skills you'll gain

R Programming
Data Analysis
Data Structures
Programming Fundamentals
Data Science
Statistical Computing
Data Manipulation
Web Scraping
Data Import
Functions

This course includes:

1.7 Hours PreRecorded video

6 quizzes, 3 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 5 modules in this course

This comprehensive course introduces beginners to R programming for data science applications. Students learn fundamental programming concepts including data types, structures, and manipulations using RStudio and Jupyter Notebooks. The curriculum covers essential topics like vectors, matrices, data frames, control flow, functions, and working with various data formats. Through hands-on labs and practical exercises, learners develop skills in reading, writing, and analyzing data while building a strong foundation in R programming.

R Basics

Module 1 · 1 Hours to complete

Common Data Structures

Module 2 · 1 Hours to complete

R Programming Fundamentals

Module 3 · 2 Hours to complete

Working with Data

Module 4 · 1 Hours to complete

Final Project

Module 5 · 3 Hours to complete

Fee Structure

Instructor

Yan Luo
Yan Luo

4.6 rating

369 Reviews

3,22,858 Students

7 Courses

AI and Machine Learning Expert at IBM Canada

Yan Luo serves as a Data Scientist and Developer at IBM Canada, where he applies his expertise in machine learning and artificial intelligence to develop innovative cognitive applications across diverse domains including software repository mining, personalized health management, wireless networks, and digital banking. After earning his Ph.D. in Machine Learning from the University of Western Ontario, he has contributed significantly to technical education through developing and teaching multiple data science courses, including Applied Data Science Capstone, Machine Learning Capstone, and Introduction to R Programming for Data Science. His work focuses on practical applications of AI and cognitive computing, bridging the gap between theoretical machine learning concepts and real-world business solutions.

Introduction to R Programming for Data Science

This course includes

10 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.5 course rating

450 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.